Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It discloses the aggregation scope ('aggregate only'), the presence of a denominator and sample provenance, and the no-per-host constraint, but says nothing about permissions, whether the operation is read-only, or response shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with zero filler; the metric and scope lead, and the parameter instruction follows. Every clause carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter aggregation tool with no output schema and no annotations, the description covers the essentials (what is measured, aggregation scope, parameter use). It stops short of describing the returned fields (denominator/sample provenance are named but not characterized) or any safety/permission context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate for the single parameter. It does: gap_class is explained as a class selector with a concrete format example (PH-C019) and clear omit-for-all behavior, which is more than the bare string schema offers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific metric (absence rate) over a specific resource (a population/table) and clarifies the scope ('Aggregate only: no per-host findings'). This separates it from host_report, though it doesn't name siblings directly and doesn't explicitly say the tool returns a computed value.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives conditional guidance for the parameter ('pass gap_class for one class; omit it for the whole table'), which is useful usage direction. However it never names an alternative tool or says when to prefer absence_rate over bulk_export or host_report, leaving the sibling routing to inference from 'no per-host findings'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.